资源开发与市场2024，Vol.40Issue(9)：1398-1409,12.DOI:10.3969/j.issn.1005-8141.2024.09.014
基于XGBoost算法的中国露营地空间分布特征及其影响因素研究
Study on the spatial distribution characteristics and influencing factors of campsites in China based on XGBoost algorithm
摘要
Abstract
The study comprehensively employed methods including nearest neighbor index,kernel density analysis,standard devia-tion ellipse,Getis-Ord G*i statistic,and XGBoost machine learning to investigate the spatial distribution patterns,influencing factors,and suitability for camping site construction in different cities of China.The results showed that:The distribution of camping sites in Chi-na exhibited an aggregation characteristic,with an overall pattern of"concentration in the east and dispersion in the west,more in the south and fewer in the north",presenting a spatial structure of"multiple cores-multiple axes".Significant regional and inter-provin-cial distribution differences existed,forming concentration areas in Beijing-Tianjin-Hebei,the Yangtze River Delta,the Pearl River Delta,and the Chengdu-Chongqing regions.The spatial distribution features of camping sites in China were comprehensively influenced by natural conditions,tourism resource endowments,and socio-economic environment.Based on the XGBoost algorithm,the influencing factors,ranked from high to low weights,were:NDVI,DEM,AQI level,GDP,number of Grade A scenic spots,domestic tourism income,road density,domestic tourism population,and wage level.Areas with high suitability for camping site construction in China were mainly concentrated in economically developed eastern regions,accounting for 48.90％of the total number;areas with moderate suitability were primarily distributed in the northwest,central,and northeast parts,with camping sites more dispersed;areas with low suitability were mainly concentrated in Qinghai and Yunnan provinces.关键词
露营地/空间分布/影响因素/XGBoost算法/适宜性分析Key words
campgrounds/spatial distribution/influencing factors/XGBoost algorithm/suitability analysis分类
管理科学引用本文复制引用
周光耀,陈心怡,赵秋皓,徐鹏飞..基于XGBoost算法的中国露营地空间分布特征及其影响因素研究[J].资源开发与市场,2024,40(9):1398-1409,12.基金项目
浙江省软科学研究计划项目(编号:2022C35090) （编号:2022C35090）
浙江省社科联项目(编号:2023N043) （编号:2023N043）
浙江农林大学科研发展基金项目(编号:2022LFR031). （编号:2022LFR031）
